Method and system for determining the condition of insured properties in a neighborhood

ABSTRACT

A method and system may determine the condition of insured properties in a neighborhood using aerial images captured from an unmanned aerial vehicle (UAV) or from a satellite device. The neighborhood may be selected by identifying a neighborhood that includes properties which are insured by a particular insurance provider. Aerial images of the entire neighborhood may then be captured and received from the UAV or the satellite device. For each insured property in the neighborhood, a condition and level of risk may be automatically determined based on the received aerial images. Then a level of risk indicator may be assigned to the insured property based on the determined level of risk. The aerial images of the insured property may be displayed on a user interface with indications of the level of risk overlaying the aerial images.

RELATED APPLICATIONS

This application is a continuation of and claims priority to U.S.application Ser. No. 14/510,307, filed on Oct. 9, 2014, entitled “Methodand System For Determining the Condition of Insured Properties in aNeighborhood,” the entire disclosure of which is hereby expresslyincorporated by reference.

TECHNICAL FIELD

The present disclosure generally relates to a method and system fordetermining the conditions of insured properties in a neighborhood and,more particularly to a method and system for performing underwriting bydetermining risk and exposures of insured or potentially insuredproperties.

BACKGROUND

During the underwriting process for property insurance, insurancecompanies evaluate the risk and exposures of potential or currentcustomers. In order to evaluate this risk, the insurance companiesassign an agent to investigate the property of a potential customer todetermine the risk and exposures of the property and to determine anappropriate premium that is commensurate with the exposure presented bythe risk.

Often, the property investigations can be time-consuming, difficult andeven dangerous for the insurance agents. For example, in order toinvestigate the risk and exposures of a home owner's roof, an agent mayhave to climb onto the roof, and perform inspections while on theowner's roof. By climbing on the roof and attempting to maneuver aroundthe roof to perform his inspection, the insurance agent opens himself toa real risk of injury, especially in difficult weather conditions wherethe roof may be slippery because of rain, snow, and/or ice and winds maybe severe.

Even if the insurance agent performs the inspection without gettinginjured, performing the full investigation may still be time-consuming.In addition to the time required to drive to and from the property andto perform the inspection itself, significant paperwork and calculationsmay be involved in calculating premium for the customers. For example,if an insurance agent takes photos on the roof of a customer's buildingin order to calculate the appropriate premium commensurate with the riskpresented by the condition of the roof, the agent may have to come backto his office, research the customer's property, compare the conditionof the customer's property to similar properties in good condition anddetermine the level of risk associated with the customer's property. Allof these steps are time consuming and both delay issuing an insurancepolicy to a customer and prevent the agent from performing underwritingfor other customers.

SUMMARY

To perform underwriting of insured or potentially insured properties ina neighborhood, an automated insurance underwriting system may identifya neighborhood with a large concentration of properties which areinsured or potentially insured by an insurance company. For example, thesystem may identify a neighborhood where over 20 percent of theproperties within the neighborhood are either insured or potentiallyinsured by the insurance company. Once the neighborhood is identified,the system may perform all insurance underwriting for the properties ina single, automatic inspection, for example by automatically surveyingthe entire neighborhood at once, instead of one property at a time.

The automatic inspection may be performed by an unmanned aerial vehicle(UAV) or by a swarm of UAVs working together, which may be controlled byan insurance agent or by the system and flown all over the neighborhoodto capture aerial images of the properties. Alternatively, the automaticinspection may be performed by a satellite which also captures aerialimages of the properties within the neighborhood. Moreover, theinspection may also be performed by a manned aerial vehicle (MAV) whichcaptures aerial images of the properties while flying over theneighborhood. Each captured aerial image may be associated with alocation, for example a GPS location, and the GPS location may be usedto determine the owner of the property which is displayed in thecaptured aerial image. If the property owner is insured by the insurancecompany, the aerial image may be used to determine the condition of theproperty as well as a level of risk associated with the property. Inthis manner, the underwriting can be performed for an insured propertywithout requiring an insurance agent to spend time and risk injury byinspecting the property. Moreover, the system provides a speedy andefficient method of performing underwriting by investigating an entireneighborhood in one inspection rather than investigating one insuredproperty at a time.

In an embodiment, a method for determining the condition of insuredproperties using aerial images is provided. The method includesidentifying that a neighborhood includes properties insured by aninsurance provider, capturing, by an aerial image capturing device, aplurality of aerial images which display the neighborhood including theinsured properties, and receiving a plurality of aerial images from theaerial image capturing device. For each of the insured properties in theidentified neighborhood, the method includes determining a condition ofthe insured property based on one or more of the plurality of aerialimages corresponding to the insured property, and determining a level ofrisk of the insured property based on the condition of the insuredproperty and a change in the condition of the insured property overtime, where the level of risk of the insured property differs accordingto a length of time that the insured property is in a particularcondition. The method further includes assigning a level of riskindicator to the insured property based on the determined level of risk,and causing the insured property to be displayed on a user interfaceincluding the level of risk indicator overlaying the insured property.Additionally, the one or more processors automatically direct the aerialimage capturing device to capture the plurality of aerial images whichdisplay the neighborhood.

In another embodiment, a system for determining the condition of insuredproperties using aerial images is provided. The system includes anaerial image capturing device which captures a plurality of aerialimages that display insured properties, a user interface, acommunication network, and one or more computing devices communicativelycoupled to the communication network, the aerial image capturing device,and the user interface. At least one of the computing devices isconfigured to identify that a neighborhood includes properties insuredby an insurance provider and receive a plurality of aerial images viathe communication network from the aerial image capturing device. Foreach of the insured properties in the identified neighborhood, at leastone of the computing devices is configured to determine a condition ofthe insured property based on one or more of the plurality of aerialimages corresponding to the insured property, and determine a level ofrisk of the insured property based on the condition of the insuredproperty and a change in the condition of the insured property overtime, where the level of risk of the insured property differs accordingto a length of time that the insured property is in a particularcondition. At least one of the computing devices is further configuredto assign a level of risk indicator to the insured property based on thedetermined level of risk, and cause the insured property to be displayedon the user interface including the level of risk indicator overlayingthe insured property. Additionally, at least one of the computingdevices automatically directs the aerial image capturing device tocapture the plurality of aerial images which display the neighborhood.

BRIEF DESCRIPTION OF THE DRAWINGS

The figures described below depict various aspects of the system andmethods disclosed therein. It should be understood that each figuredepicts an embodiment of a particular aspect of the disclosed system andmethods, and that each of the figures is intended to accord with apossible embodiment thereof. Further, wherever possible, the followingdescription refers to the reference numerals included in the followingfigures, in which features depicted in multiple figures are designatedwith consistent reference numerals.

FIG. 1A illustrates a block diagram of an example system in whichtechniques for performing automatic underwriting of insured propertiesin a neighborhood are implemented;

FIG. 1B illustrates a block diagram of an exemplary mobile device;

FIG. 2 illustrates a block diagram detailing an exemplary embodiment ofan image receiving module;

FIG. 3 depicts a block diagram detailing an exemplary embodiment of acondition assessment module;

FIG. 4 depicts a block diagram detailing an exemplary embodiment of arisk determination module;

FIG. 5 depicts an exemplary display of insured properties includinglevel of risk indicators;

FIG. 6 illustrates a flow diagram representing an exemplary method forperforming automatic insurance underwriting of insured properties in aneighborhood in accordance with the presently described embodiments.

DETAILED DESCRIPTION

Although the following text sets forth a detailed description ofnumerous different embodiments, it should be understood that the legalscope of the description is defined by the words of the claims set forthat the end of this patent and equivalents. The detailed description isto be construed as exemplary only and does not describe every possibleembodiment since describing every possible embodiment would beimpractical. Numerous alternative embodiments could be implemented,using either current technology or technology developed after the filingdate of this patent, which would still fall within the scope of theclaims.

It should also be understood that, unless a term is expressly defined inthis patent using the sentence “As used herein, the term ‘_(——————)’ ishereby defined to mean . . . ” or a similar sentence, there is no intentto limit the meaning of that term, either expressly or by implication,beyond its plain or ordinary meaning, and such term should not beinterpreted to be limited in scope based on any statement made in anysection of this patent (other than the language of the claims). To theextent that any term recited in the claims at the end of this patent isreferred to in this patent in a manner consistent with a single meaning,that is done for sake of clarity only so as to not confuse the reader,and it is not intended that such claim term be limited, by implicationor otherwise, to that single meaning. Finally, unless a claim element isdefined by reciting the word “means” and a function without the recitalof any structure, it is not intended that the scope of any claim elementbe interpreted based on the application of 35 U.S.C. § 112, sixthparagraph.

Accordingly, the term “aerial image” as used herein, may be used torefer to any image data within the electromagnetic spectrum (i.e.including the visible light spectrum as well as the invisible lightspectrum), which is captured from an elevated position. Aerial imagesmay include visible light imaging, radar imaging, near infrared imaging,thermal infrared imaging, hyperspectral imaging, multispectral imaging,full spectral imaging, etc. For example, an image captured by asatellite, a manned aerial vehicle (MAV) or an unmanned aerial vehicle(UAV) may be referred to herein as an “aerial image.” An aerial imagemay be made up of data points, for example pixel data points, where eachdata point may correspond to a specific global positioning system (GPS)location. An aerial image may also include video captured from anelevated position.

As used herein, the term “insured property” may be used to refer to anyproperty which is insured by an insurance provider. “Insured property”may include property which requires re-underwriting, because for examplethe insurance on the property is up for renewal or circumstances havechanged in such a manner that the insurance provider requiresre-underwriting. The term “potentially insured property” may be used torefer to property which the owner would like to have insured by theinsurance provider, but which must go through the underwriting processfirst before an appropriate premium can be determined and the propertycan be insured. For ease of discussion only and not for purposes oflimitation, only insured properties are mentioned below. However, theinsured properties described below may also include potentially insuredproperties.

The term “insurance provider” as used herein, generally refers to aparty or entity (e.g., a business or other organizational entity) thatprovides insurance products, e.g., by offering and issuing insurancepolicies. Typically, but not necessarily an insurance provider may be aninsurance company. Further, an insurance provider can be any individual,group of individuals, company, corporation, or other type of entity thatcan issue insurance policies for customers, such as insurance policiesassociated with properties.

An insurance provider may offer or provide one or more different typesof insurance policies. Types of insurance policies may include, forexample, homeowner's insurance; condominium owner's insurance; renter'sinsurance; business insurance (e.g., property, liability, inland marineand mobile property, etc.); insurance for catastrophic events such asflood, fire, volcano damage, etc.; personal liability insurance; andother types of insurance products. In embodiments as described herein,the insurance providers initiate and/or process claims related toinsurance policies that cover one or more properties (e.g., homes,condominiums, apartments, etc.).

Generally speaking, to perform the automatic underwriting process, anaerial image capturing device which may be a satellite, MAV, or one orseveral UAV(s) is/are directed to capture images within an identifiedneighborhood having a large percentage of properties which are insuredby an insurance provider. The aerial image capturing device may bedirected by a client device having user controls for determining thelocation and the amount of photographs or video that is captured. Thecaptured aerial images may then be provided to the client device or to aserver computer and grouped based on their GPS locations to determine agroup of aerial images which correspond to an insured property. Eachgroup of aerial images corresponding to an insured property may beaggregated, for example using photogrammetry, to create a 3-dimensional(3D) image of the insured property.

The 2D or 3D image may be displayed on the client device and may becreated at a predefined level of detail (e.g., accurate to within tenpercent) and/or may be adjustable (e.g., a user of the system may beable to “zoom in” or “zoom out” of the image). Moreover, the 2D or 3Dimage may be broken down into property components, such as a roof, adoor, siding, an exterior wall, a front lawn, a backyard, an outdoorswimming pool, a fence, a tree, a deck, a patio, etc. Each of theseproperty components may then be compared to other images of the samerespective property component for determining the condition of thecomponent. For example, an image of the roof may be compared to an imageof the roof taken ten years ago or to an image of a perfectly intactroof. The condition of each property component may be used to determinea level of risk associated with the component. Moreover, the level ofrisk may be determined independently of the condition of the propertycomponent. For example, a house with a swimming pool may create somerisk of liability regardless of the condition of the swimming pool. Thelevel of risk of each property component may be aggregated or combinedfor an insured property to determine an overall level of risk for theproperty. This overall level of risk may be provided to an insuranceagent, for example, on the user interface of the client device fordetermining an appropriate insurance premium based on the level of risk.Alternatively, the client device or the server computer mayautomatically determine an appropriate insurance premium based on thedetermined overall level of risk.

FIG. 1A illustrates various aspects of an exemplary environmentimplementing an automated insurance underwriting system 10 (alsoreferred to herein as “the system”). The system 10 may include a clientdevice 12 with remote control capabilities coupled to one or severalunmanned aerial vehicles (UAVs) 40, an MAV, a satellite device 18, and aserver 14 via a communication network 16. The client device 12 may be,for example, a laptop computer, a tablet computer, a smartphone, awearable device, etc. In the embodiment illustrated in FIG. 1A, theclient device 12 may include a central processing unit (CPU) 20, agraphics processing unit (GPU) 22, a computer-readable memory 24, and afirst user interface 30 for controlling the UAV(s) 40 or the satellitedevice 18. The first user interface 30 may include a touch interface 32,voice interface 34, etc. In various implementations, the touch interface32 can include a touchpad over which the user moves his fingers whilelooking at a separately provided screen, a touchscreen where the userplaces his fingers directly over the image being manipulated or over adisplayed control being activated (e.g. a displayed keyboard), etc. Inother implementations, the voice interface 34 may include any devicethat includes a microphone, such as a Bluetooth ear piece, a smartphone,etc. The client device 12 may further include a second user interface 70which may be used for viewing aerial images captured by the UAV(s) 40,MAV, or the satellite device 18. In some embodiments, the first userinterface 30 and the second user interface 70 may be implemented on oneuser interface which includes user controls for directing the UAV(s) 40or the satellite device 18 and displays the aerial images after theaerial images have been captured. The memory 24 is a computer-readablenon-transitory storage device that may include both persistent (e.g., ahard disk) and non-persistent (e.g., RAM) memory components, storesinstructions executable on the CPU 20 and/or the GPU 22 that make up anunderwriting evaluation module (UEM) 72, a remote control module 36 andlocation data 26 and sensor data 28 on which the remote control module36 operates. The remote control module 36 includes an incrementalmovement module 38 that allows a user to easily control the UAV(s) 40via step-like, incremental movements in which one incremental movementis in response to one single user command.

The remote control module 36 and the underwriting evaluation module 72according to various implementations operate as separately executablesoftware applications, plugins that extend the functionality of anothersoftware application such as a web browser, application programminginterfaces (API) invokable by a software application, etc. Theinstructions that make up the remote control module 36 and theunderwriting evaluation module 72 may be compiled and executable on theCPU 20 and/or the GPU 22 directly, or not compiled and interpreted bythe CPU 20 at runtime. However, FIG. 1A merely illustrates a condensedversion of the client device 12, and a more detailed version of theclient device 12 is described below with reference to FIG. 1B.

Referring still to FIG. 1A, each UAV 40 includes a controller 42 thatcommunicates with one or more proximity sensors 44, one or morestabilization sensors 45, a Global Positioning System (GPS) unit 46, animage sensor 47, and a communications unit 48. The image sensors 47 mayinclude one or more filters for infrared imaging, hyperspectral imaging,multispectral imaging, full spectral imaging, etc., or alternatively,the image sensors 47 may include one or more sensors which receive imagedata outside of the visible light spectrum such as an infrared imagesensor. The controller 42 includes a processor 50 that executesinstructions from a computer-readable memory 52 to implement a controlmodule 54 and a stabilization module 56. The control module 54 mayinvoke the stabilization module 56 to retrieve data from thestabilization sensors 45 (i.e., sensors relating avionics) to implementa control function, such as that associated with a control routine thatperforms PID (proportional-integral-derivative), fuzzy logic, nonlinear,etc. control to maintain the stability of the UAV(s) 40. For instance,the stabilization sensors 45 may include one or more of a directionalspeed sensor, a rotational speed sensors, a tilt angle sensor, aninertial sensor, an accelerometer sensor, or any other suitable sensorfor assisting in stabilization of an aerial craft. Of course, thestabilization module 56 may implement any suitable technique ofstabilizing the remote aerial device 40 in a hover or stationary threedimensional position.

The control module 54 may retrieve data from the proximity sensors 44.These proximity sensors 44 may include any sensor or technique thatassists the control module 44 in determining a distance and a directionto the insured properties within the neighborhood. The one or moreproximity sensors 44 may include optic flow sensors, ultrasonic sensors,infrared sensors, LIDAR (Light Detection and Ranging), a stereo visionsystem (SVS) that may utilize the image sensors 47 (e.g., one or morecameras) to implement stereoscopic imaging techniques to capture aerialimages of the neighborhood including the insured properties and tocreate 3D images of the insured properties. The control module 54 mayalso receive instructions from the client device 12 to capture aerialimages at specific locations or time intervals.

The GPS unit 46 may use “Assisted GPS” (A-GPS), satellite GPS, or anyother suitable global positioning protocol or system that locates theposition of the UAV(s) 40. Moreover, the GPS unit 46 may also determinethe position of the aerial images or of data points within the aerialimages captured by the UAV(s) 40, or the GPS may be combined with thedistance and direction sensors 44 to determine the position of theaerial images, and positions of data points within an aerial image. Forexample, A-GPS utilizes terrestrial cell phone towers or wi-fi hotspots(e.g., wireless router points) to more accurately and more quicklydetermine the location of the device while satellite GPS generally aremore useful in more remote regions that lack cell towers or wi-fihotspots. The communication unit 48 may communicate with the server 14or the client device 12 via any suitable wireless communication protocolnetwork, such as a wireless telephony network (e.g., GSM, CDMA, LTE,etc.), a wi-fi network (802.11 standards), a WiMAX network, a Bluetoothnetwork, etc.

As mentioned above, the system 10 may also include a satellite device 18which includes an image sensor 82 for capturing aerial images and a GPSunit 84 for determining the position of each image. For example, thesatellite device 18 may determine GPS coordinates of the boundaries ofan aerial image, and also may determine GPS coordinates of data points,such as pixel data points, of the aerial image. The satellite device 18may also include a processor 86 which executes instructions from acomputer-readable memory 88 to implement an image capturing module 90,which may capture and transmit satellite images at the request of theclient device 12. For example, the client device 12 may requestsatellite images between specified GPS coordinates, and the imagecapturing module 90 may transmit satellite images within the specifiedcoordinates. Moreover, in some embodiments the client device 12 mayspecify the number of satellite images for the image capturing module 90to capture and the zoom level. The client device 12 or the server 14 andthe satellite device 18 may communicate via a communication unit 92 viaany suitable wireless communication protocol network, such as a wirelesstelephony network (e.g., GSM, CDMA, LTE, etc.), a wi-fi network (802.11standards), a WiMAX network, a Bluetooth network, etc.

The server 14 may include insurance data (e.g., customer biographicalinformation, type of property, etc.), location data (e.g., a propertylocation of a customer, etc.), and previous image data (e.g., aerialimages of insured properties taken at an earlier date) from a customerdatabase 66, a location database 68, and a previous image database 94,respectively. The server 14 then may provide the customer data, thelocation data, the previous image data, and appropriate indications ofhow certain portions of the customer data and the location data arelinked, to the client device 12 as part of the location data 26. Theclient device 12 may use this location data to determine a geographiclocation that the UAV(s) 40 is/are initially sent to and may use theprevious image data to determine a condition of an insured property ascompared to its previous condition. Of course, the customer database 66,the location database 68, and the previous image database 94 may bedisposed within the client device 12 depending on the implementation.The server may also include a processor 60 which executes instructionsfrom a computer-readable memory 62 to implement an underwritingevaluation module 73, which may be the same as the underwritingevaluation module 72 of the client device 12. In some embodiments, theunderwriting evaluation module 72 may be disposed in the client device12, in the server 14 or in a combination of the server 14 and the clientdevice 12.

FIG. 1B illustrates the client device 12 of FIG. 1A in further detail.As illustrated in FIG. 1A, the client device may include a CPU 20, a GPU22, and a memory 24 which may be a hard drive, an optical drive, a solidstate memory device, or any other non-volatile memory device. The clientdevice 12 may further include an input/output (I/O) unit 103 and a datastorage 116, which may include customer data, location data, previousimage data, etc., which may be retrieved from software instructionswhich may be stored in the memory 24. During execution, the softwareinstructions may be stored in, and may store and retrieve data from, avolatile or non-volatile memory source, such as a random access memory(RAM) 106. The client device 12 may include a network interface module(NIM) 108 for wired and/or wireless communications. The networkinterface module 108 may allow the device to communicate with one ormore other devices such as the server 14, the satellite device 18, theMAV, or the UAV(s) 40 of FIG. 1A, by using one or more of any number ofcommunications protocols including, by way of example and notlimitation, Ethernet, cellular telephony, IEEE 802.11 (i.e., “Wi-Fi”),Fibre Channel, etc. The memory 24 may store an underwriting evaluationmodule 72 as described above. The underwriting evaluation module 72 maybe a sub-routine of a software application or may be an independentsoftware routine in and of itself. Alternatively, in someimplementations, the underwriting evaluation module 72 may be a hardwaremodule or a firmware module. The underwriting evaluation module 72 mayinclude compiled instructions directly executable by the CPU 20,scripted instructions that are interpreted at runtime, or both.

The client device may also include a user interface (UI) 118 whichincludes the remote user interface 30 and the image user interface 70 ofFIG. 1A. The remote user interface 30 may include user controls fordirecting the UAV(s) 40, for requesting aerial images from the MAV orfor requesting satellite images from the satellite device 18 at specificlocations. On the other hand, the image user interface 70 may displayaerial images of insured properties within a neighborhood and may alsodisplay levels of risk for property components of the insuredproperties.

The underwriting evaluation module (UEM) 72 may contain one or more ofan image receiving module (IRM) 115, a condition assessment module (CAM)117, and/or a risk determination module (RDM) 117. The UEM 72 maydetermine an overall level of risk associated with each insured propertyin a neighborhood according to the presently described techniques. Insome embodiments, the UEM 72 may determine a level of risk associatedwith one or more property components of an insured property. Morespecifically, the UEM 72 may automatically determine the condition ofinsured properties based on stored and received aerial images and/orother data describing property such as residential or commercialbuildings. The aerial images may be stored in the memory 24 and/or RAM106. In instances where the UEM 72 executes on a server device, thelevel of risk for an insured property may be transmitted to the clientdevice 12. Additionally, the UEM 72 may perform certain calculations onthe server device 14 of FIG. 1A while other calculations are performedon the client device 12. Moreover, the memory 24, may also include aremote control module 36 and location data 26 and sensor data 28 onwhich the remote control module 36 operates as described above withreference to FIG. 1A.

FIG. 2 is a block diagram detailing an exemplary embodiment of the imagereceiving module 115 according to the present disclosure. The imagereceiving module 115 may include a neighborhood identification module210, a filtering module 220 and an aggregation module 230. Theneighborhood identification module 210, filtering module 220 andaggregation module 230 may be separate modules or may be combined andmay interact with each other and/or with other software, hardware,and/or firmware.

The neighborhood identification module 210 may identify a neighborhoodwith a concentration of properties insured by an insurance provider thatis above a predetermined concentration threshold. For example, thepredetermined concentration threshold may be 20 percent of properties.Neighborhoods may be identified by selecting a set of boundaries whichencapsulate the neighborhood and determine the number of propertieswhich are insured by the insurance provider as compared to the number ofproperties which are not insured by the insurance provider within theset of boundaries. For example, the set of boundaries may be GPScoordinates or alternatively a radius may be specified from a centerpoint within the neighborhood. In any event, when a neighborhood isidentified with a concentration of insured properties that exceeds theconcentration threshold, the underwriting evaluation module 72 mayrequest and/or receive aerial images of the identified neighborhood. Forexample, the underwriting evaluation module 72 may receive the aerialimages of the identified neighborhood from the satellite device 18 ofFIG. 1A, the MAV, or from the UAV(s) 40. The aerial images may bereceived from the UAV(s) 40 by automatically directing the one orseveral UAV(s) 40 to fly within the set of boundaries which encapsulatethe identified neighborhood. The UAV(s) 40 may also be directed to takeseveral photographs at different locations within the neighborhood andat several angles. Alternatively, after the neighborhood is identified,a user such as an insurance agent may control the UAV(s) 40 remotely,through a series of user controls on the remote user interface 30 tocause the UAV(s) to take pictures at different locations within theneighborhood and at several angles.

After the aerial images are captured and received for the identifiedneighborhood, the underwriting evaluation module 72 may use thefiltering module 220 to filter out aerial images that do not displayinsured properties, and to group together all of the aerial images whichdisplay a single insured property. For example, the filtering module 220may use the customer data and the location data stored in the datastorage entity 116 or the customer database 66 and the location database68 of the server 14 to determine the locations of insured properties.The locations of insured properties may be compared to a received aerialimage which contains GPS coordinates of its data points, as describedabove, to determine whether the received aerial image displays aninsured property. For example, if the location of the aerial imagesmatches with one of the locations of the insured properties then theaerial image displays an insured property. If the received aerial imagedoes not display any insured properties the aerial image may bediscarded. Otherwise, the filtering module 220 may group the remainingreceived aerial images with other aerial images which display the sameinsured property. In some embodiments, an aerial image may display morethan one insured property. In this instance, the aerial image may begrouped with each of the insured properties that the image displays.

Each group of aerial images which displays the same insured property maybe combined using an aggregation module 230. The group of aerial imagesmay be combined to generate a 3D image of the insured property using 3Dimaging techniques such as stereoscopy or photogrammetry. Theaggregation module 230 may utilize the Cartesian or GPS coordinatesreceived with each aerial image to reconstruct a 3D image of the insuredproperty using the group of aerial images captured at differentlocations and angles. The aggregation module 230 may combine each groupof aerial images to generate a 3D aerial image of each insured propertyin the neighborhood.

FIG. 3 is a block diagram detailing an exemplary embodiment of thecondition assessment module 117. The condition assessment module 117 mayinclude a component recognition module 310, a comparison module 320 anda condition determination module 330. In some embodiments, the conditionassessment module 117 may obtain a 3D aerial image of an insuredproperty and determine the condition of the insured property. In otherembodiments, the condition assessment module 117 does not obtain 3Daerial images and instead obtains 2D aerial images. Moreover, in someembodiments, the 3D aerial image may be obtained from the imagereceiving module 115. The condition assessment module 117 may obtain one3D aerial image of an insured property at a time or alternatively mayobtain several 3D aerial images depicting each of the insured propertiesin a neighborhood.

In any event, the component recognition module 310 may determineproperty components of a 3D aerial image of an insured property.Property components may include a roof, a door, a window, siding,exterior walls, a lawn, a backyard, an outdoor swimming pool, a fence, atree, a deck, a patio, etc. The component recognition module 310 maydetermine a portion of the 3D aerial image of the insured property whichdisplays a particular property component. For example, the componentrecognition module 310 may determine a door of the insured property bydetermining the data points in the 3D aerial image which include thedoor. Various image processing techniques such as edge detection may beused by the component recognition module 310 for determining the datapoints of a 3D aerial image which depict a particular propertycomponent.

Once the property components are determined for a 3D aerial image or forseveral 3D aerial images in a neighborhood, each property component maybe compared with other predefined property components using thecomparison module 320. The comparison module 320 may compare the datapoints of a property component with data describing one or morepredefined property components corresponding to the same propertycomponent. If the property component is a roof, for example, thecomparison module 320 may compare data extracted by the componentrecognition module 310 with previously stored images of brand-new“stock” tiles and of an intact roof. Based on these comparisons, thecomparison module 320 may determine physical differences between theroof depicted in the data points and the stock components (e.g., brandnew roof tiles). For example, the comparison module 320 may determinethat the data points depicting the roof differ in color (e.g., due toweather aging), thickness (e.g., due to cracks or dents in the surface),and/or in height/width (e.g., due to chipping on one or more edges) fromthe brand-new “stock” tiles.

Moreover, the comparison module 320 may also compare the data depictinga roof with a previously stored image of the same roof, for example,from five years ago. The previously stored image of the same roof may beobtained from the previous image data 94 stored at the server 14 or theclient device 12 of FIG. 1A. After an aerial image of insured propertyis captured, the aerial image may be stored in the previous image data94, so that it may be compared with a newly captured image of the sameproperty at a later date. In this manner, the degradation/maintenance ofan insured property or of a property component may be determined overtime for a more detailed analysis of the level of risk of the insuredproperty. Moreover, the aerial images may display the presence of newrooms or structures which were not present in the previous aerial imagesof the insured property. This may allow the system to detect additionalrisk as compared to the previous state of the insured property duringthe re-underwriting process. Comparing the newly captured images of theinsured property to previously captured images may also allow the systemto determine the age of property components, e.g., the aerial images maydisplay the roof being replaced ten years ago.

After comparisons have been made for each property component in aninsured property or in a neighborhood, a condition determination module330 may determine the condition of each property component based on thecomparison. Conditions may include condition categories such as “poor,”“fair,” “moderate,” “good,” “excellent,” etc., or may include numericalcondition scores, for example from a scale of one to one hundred. Forexample, with reference to the roof example described above, a roofhaving several cracks or dents in the surface may be determined to be inpoor condition.

Each property component along with the respective condition determinedfor each property component may then be provided to a risk determinationmodule, such as the risk determination module 119 as depicted in FIG. 4.The risk determination module 119 may include a level of riskdetermination module 410, and a risk indicator module 420. The level ofrisk determination module 410 may determine that a property componentbelongs to a particular level of risk category from a set of level ofrisk categories. For example, the set of level of risk categories mayinclude “low,” “moderate,” “high,” “liability,” “very low,” “very high,”etc. In other embodiments, the level of risk determination module 410may determine a level risk score for a property component, such as anumeric level of risk score on a scale from one to ten.

In any event, the level of risk determination module 410 may determinethe level of risk for a property component based, at least in part, onthe condition of the property component. For example, a door in poorcondition may have a higher level of risk than a door in excellentcondition. However, the condition of the property component may not bethe only factor considered by the level of risk determination module 410for determining the level of risk. The maintenance of the propertycomponent may also be used for determining its level of risk. Forexample, a roof in moderate condition that has been in the same moderatecondition for 15 years and has not worsened may have a lower level ofrisk than a roof in moderate condition for the first time. On the otherhand, the level of risk may be higher for the roof that has been inmoderate condition for 15 years because it may be more likely that theroof will be downgraded to poor condition than the roof in moderatecondition for the first time. The type of property component may also bea factor for determining the level of risk, regardless of the propertycomponent's condition. For example, a swimming pool may pose a highlevel of risk even if it is kept in excellent condition, because of theliability risk associated with a swimming pool. Moreover, a gas line ina home or a forest in a backyard may pose fire risks even when they areproperly maintained. However, this is merely an exemplary list offactors which may be considered by the level of risk determinationmodule 410 for determining the level of risk. Any number of additionalfactors may also be considered and some of the factors mentioned abovemay be omitted by the level of risk determination module 410. In someembodiments, the level of risk determination module 410 may include aset of rules which may be used for each property component to determineits level of risk. The set of rules may include the factors mentionedabove or any number of additional factors. In some embodiments, the setof rules may include combining and/or aggregating the factors which areapplied to a property component to determine a level of risk for theproperty component. In an embodiment, the set of rules may be determinedbased on heuristics, best practices and/or statistical data.

In any event, once the level of risk is determined for each propertycomponent or alternatively once the level of risk is determined for asingle property component, the risk indicator module 420 may assign alevel of risk indicator to each property component. For example, eachlevel of risk category from the set of level of risk categories may beassigned a respective level of risk indicator. More specifically, the“moderate” risk category may correspond to the color yellow, forexample. Moreover, the “high” risk category may correspond to the colorred, and the “low” risk category may correspond to the color green. Inother embodiments, a range of level of risk scores may be assigned alevel of risk indicator. For example, level of risk scores between 1 and3 may correspond to the color green. The corresponding level of riskindicators may then be assigned to each property component based on thedetermined level of risk for the property component. For example, apiece of siding with a moderate level of risk may be assigned the coloryellow. An assigned level of risk indicator for a property component maythen be appended to one or more aerial images which may be 3D aerialimages and which display the property component. For example, an aerialimage displaying the piece of siding may display the color yellowoverlaying the piece of siding.

While the level of risk indicators are described as the colors red,green and yellow, the indicators are not limited to those particularcolors. Instead, the level of risks indicators may include any color andalso may include any other suitable representation of a level of risk.For example, level of risk indicators may include numbers which areplaced over each property component, may include labels which indicatethe level of risk category for each property component, may includesymbols which indicate the level of risk category for each propertycomponent, may include different shading techniques which indicate thelevel of risk category for each property component, etc.

The aerial images which display insured properties and include level ofrisk indicators may then be displayed on the client device 12 for aninsurance agent to view. In some embodiments, the client device 12 maydisplay a 3D aerial image of an insured property with level of riskindicators overlaying each property component. Moreover, in someembodiments, the client device 12 may display several aerial images fora single insured property and include the level of risk indicators foreach property component. As mentioned above, some aerial images maydisplay more than one insured property and as a result, may be includedin both sets of aerial images which display a first and a second insuredproperty, respectively.

In some embodiments, the underwriting evaluation module 72 may include aset of rules for determining an insurance premium based on the levels ofrisk of the various property components corresponding to an insuredproperty. For example, the underwriting evaluation module 72 mayaggregate and/or combine the level of risk categories or the level ofrisk scores to determine an overall level of risk. The overall level ofrisk may be used to determine an appropriate insurance premium. In otherembodiments, an insurance agent or a user of the client device 12 mayview the levels of risk of the various property components to determinethe appropriate insurance premium for the insured property.

FIG. 5 illustrates an exemplary display 500 from an aerial image ofinsured properties including level of risk indicators. In someembodiments, the display 500 may be presented on the image userinterface 70 of the client device 12 of FIG. 1A. In other embodiments,the display 500 may be presented on another computing device. Thedisplay 500 may include a legend 502 which explains the meaning of eachlevel of risk indicator present on the display 500. For example, thelegend 502 explains a red color indicates “high risk,” a yellow colorindicates “moderate risk,” and a green color indicates “low risk.”Moreover, the display 500 may also include a key 504 describing theproperty components which were identified for each level of riskcategory. For example, the key 504 describes a swimming pool and poorroof are identified as high risk, a forest and dry timber are identifiedas moderate risk because they are considered fire hazards, and the areasurrounding the pool is identified as low risk because of the liabilityassociated with a wet deck or a pool.

Additionally, the display 500 may include two insured properties, afirst insured property 516 and a second insured property 518. Thedisplay 500 of the first insured property 516 may include the propertycomponents: a roof 506, a swimming pool 510, a pool deck 512, a backyard514, windows 520 and siding 522. The first insured property 516 may alsoinclude additional property components which may be shown more clearlyin another display at a different angle, location and/or zoom level.

In any event, the roof 506 is identified as being in poor condition,which may be determined from the condition assessment module 117 of FIG.3. As a result, the roof 506 in poor condition is identified as highrisk which may be determined from the risk determination module 119 ofFIG. 4, and assigned a red level of risk indicator. The red color isplaced over the roof 506 on the display 500 to indicate high risk.Moreover, the swimming pool 510 is also assigned the red level of riskindicator to indicate high risk. While the key 504 does not explain thatthe swimming pool 510 is in poor or even moderate condition, theswimming pool 510 may be identified as high risk because of the inherentdangers associated with a pool, e.g., injuries in the pool, drowning,flooding, etc. The backyard 514 is identified as moderate risk andassigned a yellow level of risk indicator, because of the fire hazardsassociated with the forestry in the backyard 514. Further, the pool deck512 is identified as low risk, because of the liability risks associatedwith a pool and the surrounding areas such as a wet deck.

The windows 520 and siding 522 are not identified as having any level ofrisk. This may be because of the excellent condition and/or maintenance.However, the windows 520 and siding 522 also may not be identified ashaving any level of risk because of the angle, location, and/or zoomlevel of the display 500. Other aerial images may capture a closer, moredetailed version of the windows 520 and siding 522, and the display fromthose aerial images may include a level of risk.

The second insured property 518 also includes a red level of riskindicator assigned to the roof 508 as well as a yellow level of riskindicator assigned to the backyard because of the forestry. As mentionedabove, each aerial image may be grouped into a set of aerial imageswhich display a single insured property. In this instance, the aerialimage of the display 500 may belong to the set of aerial images whichdisplay the first insured property 516 and to the set of aerial imageswhich display the second insured property 518. Moreover, each insuredproperty 516, 518 may include several aerial images which may be takenfrom different angles, at different zoom levels, and at differentlocations in order to capture the complete insured property. The aerialimage of the display 500 may be just one of several images of theinsured properties 516, 518.

FIG. 6 illustrates a flow diagram representing an exemplary method 600for performing automatic insurance underwriting of insured properties ina neighborhood. The method 600 may be executed on the client device 12,the server computer 14 or some combination of the client device 12 andthe server computer 14. For example, at least a portion of the method600 may be performed by the underwriting evaluation module 72 of FIG. 1Awhich as mentioned above, may be disposed on the client device 12, theserver computer 14 or some combination of the client device 12 and theserver computer 14. In an embodiment, the underwriting evaluation module72 may include computer-executable instructions stored on one or morenon-transitory, tangible, computer-readable storage media or devices,and the computer-executable instructions of the underwriting evaluationmodule 72 may be executed to perform the method 600.

At block 602, a neighborhood may be identified which includes a largeconcentration of insured properties. In some embodiments, theneighborhood may be identified by comparing its concentration of insuredproperties to a predetermined threshold. For example, neighborhoodshaving more than 20 percent of properties insured by the same insuranceprovider may be identified as having a large concentration of insuredproperties. Neighborhoods may be identified by selecting a set ofboundaries which encapsulate the neighborhood and determining the numberof properties which are insured by the insurance provider as compared tothe number of properties which are not insured by the insurance providerwithin the set of boundaries. For example, the set of boundaries may beGPS coordinates or alternatively a radius may be specified from a centerpoint within the neighborhood.

Then, aerial images which display the insured properties in theneighborhood may be received (block 604). The aerial images may bereceived from the satellite device 18, the MAV, or the UAV(s) 40 of FIG.1A. In some embodiments, user controls may be disposed on the clientdevice 12 which allow a user, such as an insurance agent, to control theUAV(s) 40 remotely and determine when and where to capture aerialimages. In other embodiments, the UAV(s) 40 may be preprogrammed tocapture aerial images at specified locations. Additionally, in someembodiments, the satellite device 18 or the UAV(s) 40 may capture aerialimages of the entire neighborhood. A filter such as the filtering module220 of FIG. 2 may only allow those aerial images which display aninsured property to pass through the filter based on the location ofeach aerial image.

At block 606, the underwriting evaluation module 72 may determine a setof aerial images which display a particular insured property of theseveral insured properties in the neighborhood. For example, thelocation of the particular insured property may be determined. Then eachaerial image which displays the same location as the insured propertymay be grouped into the set of aerial images which display theparticular insured property. In some embodiments, when an aerial imagedisplays more than one insured property, the aerial image is groupedinto the set of aerial images for each insured property it displays.Moreover, in some embodiments, the set of aerial images may beaggregated to form a 3D display of the particular insured property. Forexample, the set of aerial images may be aggregated using photogrammetrytechniques to create the 3D image.

Then, the condition of the particular insured property may be determinedbased on the set of aerial images which display the particular insuredproperty (block 608). In some embodiments, the particular insuredproperty may be divided into several property components and a conditionmay be determined for each property component. The condition may bedetermined by comparing the property component to a previous image ofthe property component taken at an earlier date. Additionally, thecondition may be determined by comparing the property component to asimilar property component in good condition and identifying differencesbetween the two. Moreover, the condition may be determined based on theage of the particular insured property, the level of maintenance of theparticular insurance property, changes to the particular insuredproperty, etc. In an embodiment, an overall condition of the insuredproperty may be determined based on the condition of each propertycomponent.

Based at least in part on the condition of the particular insuredproperty, a level of risk may be determined (block 610). For example, alevel of risk score or a level of risk category may be determined foreach property component of the particular insured property. The level ofrisk score or category may be determined for a property component basedon the condition of the property component, the level of maintenance ofthe property component, inherent dangers associated with the propertycomponent, etc. Additionally, the level of risk score or category may bedetermined using a set of rules. A level of risk indicator may then beassigned to each property component based on the determined level ofrisk. Moreover, in some embodiments, the level of risk indicators may bedisplayed along with a display of the aerial images for the particularinsured property, for example, on the client device 12.

At block 612, the underwriting evaluation module 72 may determinewhether or not a level of risk has been determined for all of theinsured properties in the neighborhood. If a level of risk has not beendetermined for every insured property, the method 600 continues at block606 and a set of aerial images which display another insured property inthe neighborhood is determined. Otherwise, if a level of risk has beendetermined for every insured property, the process ends.

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Additionally, certain embodiments are described herein as includinglogic or a number of routines, subroutines, applications, orinstructions. These may constitute either software (e.g., code embodiedon a machine-readable medium or in a transmission signal) or hardware.In hardware, the routines, etc., are tangible units capable ofperforming certain operations and may be configured or arranged in acertain manner. In example embodiments, one or more computer systems(e.g., a standalone, client or server computer system) or one or morehardware modules of a computer system (e.g., a processor or a group ofprocessors) may be configured by software (e.g., an application orapplication portion) as a hardware module that operates to performcertain operations as described herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that is permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC)) toperform certain operations. A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. Considering embodiments inwhich hardware modules are temporarily configured (e.g., programmed),each of the hardware modules need not be configured or instantiated atany one instance in time. For example, where the hardware modulescomprise a general-purpose processor configured using software, thegeneral-purpose processor may be configured as respective differenthardware modules at different times. Software may accordingly configurea processor, for example, to constitute a particular hardware module atone instance of time and to constitute a different hardware module at adifferent instance of time.

Hardware modules can provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multipleof such hardware modules exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the hardware modules. In embodiments in whichmultiple hardware modules are configured or instantiated at differenttimes, communications between such hardware modules may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware modules have access. Forexample, one hardware module may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware module may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processor-implemented. For example, at least some of theoperations of a method may be performed by one or more processors orprocessor-implemented hardware modules. The performance of certain ofthe operations may be distributed among the one or more processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processor or processors maybe located in a single location (e.g., within a home environment, anoffice environment or as a server farm), while in other embodiments theprocessors may be distributed across a number of locations.

The performance of certain of the operations may be distributed amongthe one or more processors, not only residing within a single machine,but deployed across a number of machines. In some example embodiments,the one or more processors or processor-implemented modules may belocated in a single geographic location (e.g., within a homeenvironment, an office environment, or a server farm). In other exampleembodiments, the one or more processors or processor-implemented modulesmay be distributed across a number of geographic locations.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein any reference to “one embodiment” or “an embodiment”means that a particular element, feature, structure, or characteristicdescribed in connection with the embodiment is included in at least oneembodiment. The appearances of the phrase “in one embodiment” in variousplaces in the specification are not necessarily all referring to thesame embodiment.

Some embodiments may be described using the expression “coupled” and“connected” along with their derivatives. For example, some embodimentsmay be described using the term “coupled” to indicate that two or moreelements are in direct physical or electrical contact. The term“coupled,” however, may also mean that two or more elements are not indirect contact with each other, but yet still co-operate or interactwith each other. The embodiments are not limited in this context.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

In addition, use of the “a” or “an” are employed to describe elementsand components of the embodiments herein. This is done merely forconvenience and to give a general sense of the description. Thisdescription, and the claims that follow, should be read to include oneor at least one and the singular also includes the plural unless it isobvious that it is meant otherwise.

This detailed description is to be construed as exemplary only and doesnot describe every possible embodiment, as describing every possibleembodiment would be impractical, if not impossible. One could implementnumerous alternate embodiments, using either current technology ortechnology developed after the filing date of this application.

We claim:
 1. A method for determining the condition of insured properties using aerial images, the method executed by one or more processors programmed to perform the method, the method comprising: identifying, by the one or more processors, that a neighborhood includes properties insured by an insurance provider; capturing, by an aerial image capturing device, a plurality of aerial images which display the neighborhood including the insured properties; receiving, at the one or more processors, a plurality of aerial images from the aerial image capturing device; and for each of the insured properties in the identified neighborhood: determining, by the one or more processors, a condition of the insured property based on one or more of the plurality of aerial images corresponding to the insured property; determining, by the one or more processors, a level of risk of the insured property based on the condition of the insured property and a change in the condition of the insured property over time, wherein the level of risk of the insured property differs according to a length of time that the insured property is in a particular condition; assigning, by the one or more processors, a level of risk indicator to the insured property based on the determined level of risk; and causing, by the one or more processors, the insured property to be displayed on a user interface including the level of risk indicator overlaying the insured property; wherein the one or more processors automatically direct the aerial image capturing device to capture the plurality of aerial images which display the neighborhood.
 2. The method of claim 1, further comprising: determining, by the one or more processors, a location of each of the received plurality of aerial images; and filtering, by the one or more processors, the plurality of aerial images based on the determined locations to determine a subset of the plurality of aerial images, wherein each aerial image in the subset displays at least one insured property; and for each of the insured properties in the identified neighborhood, determining one or more aerial images of the subset of the plurality of aerial images which display at least a portion of the insured property.
 3. The method of claim 1, wherein the aerial image capturing device is an unmanned aerial vehicle.
 4. The method of claim 3, further comprising: directing, by the one or more processors, the unmanned aerial vehicle to one or more locations for capturing the plurality of aerial images.
 5. The method of claim 1, wherein assigning the level of risk indicator to the insured property includes assigning a first level of risk indicator corresponding to a first portion of the insured property, and assigning a second level of risk indicator corresponding to a second portion of the insured property, wherein the second level of risk indicator is different from the first level of risk indicator.
 6. The method of claim 1, further comprising: for each of the insured properties in the identified neighborhood, aggregating the respective one or more aerial images corresponding to the insured property to generate a three dimensional display of the insured property on a user interface; and wherein determining the condition of the insured property includes determining the condition of the insured property based on the three dimensional display.
 7. The method of claim 1, wherein determining the condition of the insured property includes determining a separate condition for one or more property components of the insured property.
 8. The method of claim 7, wherein the one or more property components include at least one of: a window, a door, a roof, siding, an exterior wall, a garage, a backyard, a swimming pool, a lawn, a driveway, a fence, a tree, a deck, or a patio.
 9. The method of claim 1, wherein the aerial image capturing device includes one or more stabilization sensors which control aerial movement of the aerial image capturing device and an image sensor.
 10. The method of claim 1, wherein determining the change in the condition of the insured property over time includes comparing the respective one or more aerial images corresponding to the insured property to one or more historical images of the insured property, wherein the historical images were captured before the respective one or more aerial images.
 11. The method of claim 10, wherein determining the condition of the insured property includes determining at least one of: an age of the insured property or a level of maintenance for the insured property.
 12. A system for determining the condition of insured properties in a neighborhood, the system comprising: an aerial image capturing device which captures a plurality of aerial images that display insured properties; a user interface; a communication network; and one or more computing devices communicatively coupled to the communication network, the aerial image capturing device, and the user interface, each of the one or more computing devices having a memory and one or more processors and at least one of the computing devices configured to: identify that a neighborhood includes properties insured by an insurance provider; receive a plurality of aerial images via the communication network from the aerial image capturing device; and for each of the insured properties in the identified neighborhood: determine a condition of the insured property based on one or more of the plurality of aerial images corresponding to the insured property; determine a level of risk of the insured property based on the condition of the insured property and a change in the condition of the insured property over time, wherein the level of risk of the insured property differs according to a length of time that the insured property is in a particular condition; assign a level of risk indicator to the insured property based on the determined level of risk; and cause the insured property to be displayed on the user interface including the level of risk indicator overlaying the insured property; wherein the at least one computing device automatically directs the aerial image capturing device to capture the plurality of aerial images which display the neighborhood.
 13. The system of claim 12, wherein the at least one computing device is further configured to: determine a location of each of the received plurality of aerial images; and filter the plurality of aerial images based on the determined locations to determine a subset of the plurality of aerial images, wherein each aerial image in the subset displays at least one insured property; and for each of the insured properties in the identified neighborhood, determine one or more aerial images of the subset of the plurality of aerial images which display at least a portion of the insured property.
 14. The system of claim 12, wherein the aerial image capturing device is an unmanned aerial vehicle.
 15. The system of claim 14, wherein the at least one computing device is further configured to: direct the unmanned aerial vehicle to one or more locations for capturing the plurality of aerial images.
 16. The system of claim 14, wherein the at least one computing device is further configured to: display one or more user controls on the user interface configured to receive directions for navigating the unmanned aerial vehicle.
 17. The system of claim 12, wherein to assign the level of risk indicator to the insured property, the at least one computing device is configured to assign a first level of risk indicator corresponding to a first portion of the insured property, and assign a second level of risk indicator corresponding to a second portion of the insured property, wherein the second level of risk indicator is different from the first level of risk indicator.
 18. The system of claim 12, wherein the at least one computing device is further configured to: for each of the insured properties in the identified neighborhood: aggregate the respective one or more aerial images corresponding to the insured property to generate a three dimensional display of the insured property on the user interface; and wherein to determine the condition of each insured property, the at least one computing device is configured to determine the condition of the insured property based on the three dimensional display.
 19. The system of claim 12, wherein to determine the condition of each insured property, the at least one computing device is configured to determine a separate condition for one or more property components of the insured property.
 20. The system of claim 12, wherein the aerial image capturing device includes one or more stabilization sensors which control aerial movement of the aerial image capturing device and an image sensor. 